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1,034 results for “Empirical”
Data from: A mechanistic and empirically-supported lightning risk model for forest trees
<ol> <li>Tree death due to lightning influences tropical forest carbon cycling and tree community dynamics. However, the distribution of lightning damage among trees in forests remains poorly understood. </li> <li>We developed models to predict direct and secondary lightning damage to trees based on tree size, crown exposure, and local forest structure. We parameterized these models using data on the locations of lightning strikes and censuses of tree damage in strike zones, combined with drone-based maps of tree crowns and censuses of all trees within a 50-ha forest dynamics plot on Barro Colorado Island, Panama. </li> <li>The likelihood of a direct strike to a tree increased with larger exposed crown area and higher relative canopy position (emergent > canopy >>> subcanopy), whereas the likelihood of secondary lightning damage increased with tree diameter and proximity to neighboring trees. The predicted frequency of lightning damage in this mature forest was greater for tree species with larger average diameters.</li> <li>These patterns suggest that lightning influences forest structure and the global carbon budget by nonrandomly damaging large trees. Moreover, these models provide a framework for investigating the ecological and evolutionary consequences of lightning disturbance in tropical forests.</li> </ol> <p><b>Synthesis:</b> Our findings indicate that the distribution of lightning damage is stochastic at large spatial grain and relatively deterministic at smaller spatial grain (<15 m). Lightning is more likely to directly strike taller trees with large crowns and secondarily damage large neighboring trees that are closest to the directly struck tree. The results provide a framework for understanding how lightning can affect forest structure, forest dynamics, and carbon cycling. The resulting lightning risk model will facilitate informed investigations into the effects of lightning in tropical forests.</p>
Data from: The contribution of maternal effects to selection response: an empirical test of competing models
Maternal effects can dramatically influence the evolutionary process, in some cases facilitating and in others hindering adaptive evolution. Maternal effects have been incorporated into quantitative genetic models using two theoretical frameworks: the variance-components approach, which partitions variance into direct and maternal components, and the trait-based approach, which assumes that maternal effects are mediated by specific maternal traits. Here, we demonstrate parallels between these models and test their ability to predict evolutionary change. First, we show that the two approaches predict equivalent responses to selection in the absence of maternal effects mediated by traits that are themselves maternally influenced. We also introduce a correction factor that may be applied when such cascading maternal effects are present. Second, we use several maternal effect models, as well as the standard breeder's equation, to predict evolution in response to artificial selection on flowering time in American bellflower, Campanulastrum americanum. Models that included maternal effects made much more accurate predictions of selection response than the breeder's equation. Maternal effect models differed somewhat in their fit, with a version of the trait-based model providing the best fit. We recommend fitting such trait-based models when possible and appropriate to make the most accurate evolutionary predictions.
Data from: Effect of microsatellite selection on individual and population genetic inferences: an empirical study using cross-specific and species-specific amplifications
Although whole-genome sequencing is becoming more accessible and feasible for nonmodel organisms, microsatellites have remained the markers of choice for various population and conservation genetic studies. However, the criteria for choosing microsatellites are still controversial due to ascertainment bias that may be introduced into the genetic inference. An empirical study of red deer (Cervus elaphus) populations, in which cross-specific and species-specific microsatellites developed through pyrosequencing of enriched libraries, was performed for this study. Two different strategies were used to select the species-specific panels: randomly vs. highly polymorphic markers. The results suggest that reliable and accurate estimations of genetic diversity can be obtained using random microsatellites distributed throughout the genome. In addition, the results reinforce previous evidence that selecting the most polymorphic markers leads to an ascertainment bias in estimates of genetic diversity, when compared with randomly selected microsatellites. Analyses of population differentiation and clustering seem less influenced by the approach of microsatellite selection, whereas assigning individuals to populations might be affected by a random selection of a small number of microsatellites. Individual multilocus heterozygosity measures produced various discordant results, which in turn had impacts on the heterozygosity-fitness correlation test. Finally, we argue that picking the appropriate microsatellite set should primarily take into account the ecological and evolutionary questions studied. Selecting the most polymorphic markers will generally overestimate genetic diversity parameters, leading to misinterpretations of the real genetic diversity, which is particularly important in managed and threatened populations.
An empirical evaluation of camera trap study design: how many, how long, and when?
1. Camera traps deployed in grids or stratified random designs are a well-established survey tool for wildlife but there has been little evaluation of study design parameters. 2. We used an empirical subsampling approach involving 2225 camera deployments run at 41 study areas around the world to evaluate three aspects of camera trap study design (number of sites, duration and season of sampling) and their influence on the estimation of three ecological metrics (species richness, occupancy, detection rate) for mammals. 3. We found that 25-35 camera locations were needed for precise estimates of species richness, depending on scale of the study. The precision of species-level estimates of occupancy was highly sensitive to occupancy level, with <20 camera sites needed for precise estimates of common (>0.75) species, but more than 150 sites likely needed for rare (<0.25) species. Species detection rates were more difficult to estimate precisely at the grid level due to spatial heterogeneity, presumably driven by unaccounted for habitat variability within the study area. Running a camera at a site for 2 weeks was most efficient for detecting new species, but 3-4 weeks were needed for precise estimates of local detection rate, with no gains in precision observed after 1 month. Metrics for all mammal communities were sensitive to seasonality, with 37-50% of the species at the sites we examined fluctuating significantly in their occupancy or detection rates over the year. This effect was more pronounced in temperate sites, where seasonally sensitive species varied in relative abundance by an average factor of 4-5, and some species were completely absent in one season due to hibernation or migration. 4. We recommend the following guidelines to efficiently obtain precise estimates of species richness, occupancy and detection rates with camera trap arrays: run each camera for 3-5 weeks across 40-60 sites per array. We recommend comparisons of detection rates be model-based and include local covariates to help account for small-scale variation. Furthermore, comparisons across study areas or times must account for seasonality, which had strong impacts on mammal communities in both tropical and temperate sites.
Data from: Do genetic drift and accumulation of deleterious mutations preclude adaptation? Empirical investigation using RADseq in a northern lacustrine fish
Understanding genomic signatures of divergent selection underlying long-term adaptation in populations located in heterogeneous environments is a key goal in evolutionary biology. In this study, we investigated neutral, adaptive and deleterious genetic variation using 7,192 SNPs in 31 Lake Trout (Salvelinus namaycush) populations (n = 673) from Québec, Canada. Average genetic diversity was low, weakly shared among lakes, and positively correlated to lake size, indicating a major role for genetic drift subsequent to lake isolation. Putatively deleterious mutations were on average at lower frequencies than the other SNPs, and their abundance relative to the entire polymorphism in each population was positively correlated to inbreeding, suggesting that the effectiveness of purifying selection was negatively correlated to inbreeding, as predicted from theory. Despite evidence for pronounced genetic drift and inbreeding, several outlier loci were associated with temperature and found in or close to genes with biologically relevant functions notably related to heat-stress and immune responses. Outcomes of gene-temperature associations were influenced by the inclusion of the most inbred populations, in which allele frequencies deviated the most from model predictions. This result illustrates challenge in identifying gene-environment associations in cases of high genetic drift and restricted gene flow and suggests limited adaptation in populations experiencing higher inbreeding. We discuss the relevance of these findings for the conservation and management, notably regarding stocking and genetic rescue, of Lake Trout populations and other species inhabiting highly fragmented habitats.
Data from: Correcting for cell-type effects in DNA methylation studies: reference-based method outperforms latent variable approaches in empirical studies
Based on an extensive simulation study, McGregor and colleagues recently recommended the use of surrogate variable analysis (SVA) to control for the confounding effects of cell-type heterogeneity in DNA methylation association studies in scenarios where no cell-type proportions are available. As their recommendation was mainly based on simulated data, we sought to replicate findings in two large-scale empirical studies. In our empirical data, SVA did not fully correct for cell-type effects, its performance was somewhat unstable, and it carried a risk of missing true signals caused by removing variation that might be linked to actual disease processes. By contrast, a reference-based correction method performed well and did not show these limitations. A disadvantage of this approach is that if reference methylomes are not (publicly) available, they will need to be generated once for a small set of samples. However, given the notable risk we observed for cell-type confounding, we argue that, to avoid introducing false-positive findings into the literature, it could be well worth making this investment.
Data from: Empirical and Bayesian approaches to fossil-only divergence times: a study across three reptile clades
Estimating divergence times on phylogenies is critical in paleontological and neontological studies. Chronostratigraphically-constrained fossils are the only direct evidence of absolute timing of species divergence. Strict temporal calibration of fossil-only phylogenies provides minimum divergence estimates, and various methods have been proposed to estimate divergences beyond these minimum values. We explore the utility of simultaneous estimation of tree topology and divergence times using BEAST tip-dating on datasets consisting only of fossils by using relaxed morphological clocks and birth-death tree priors that include serial sampling (BDSS) at a constant rate through time. We compare BEAST results to those from the traditional maximum parsimony (MP) and undated Bayesian inference (BI) methods. Three overlapping datasets were used that span 250 million years of archosauromorph evolution leading to crocodylians. The first dataset focuses on early Sauria (31 taxa, 240 chars.), the second on early Archosauria (76 taxa, 400 chars.) and the third on Crocodyliformes (101 taxa, 340 chars.). For each dataset three time-calibrated trees (timetrees) were calculated: a minimum-age timetree with node ages based on earliest occurrences in the fossil record; a 'smoothed' timetree using a range of time added to the root that is then averaged over zero-length internodes; and a tip-dated timetree. Comparisons within datasets show that the smoothed and tip-dated timetrees provide similar estimates. Only near the root node do BEAST estimates fall outside the smoothed timetree range. The BEAST model is not able to overcome limited sampling to correctly estimate divergences considerably older than sampled fossil occurrence dates. Conversely, the smoothed timetrees consistently provide node-ages far older than the strict dates or BEAST estimates for morphologically conservative sister-taxa when they sit on long ghost lineages. In this latter case, the relaxed-clock model appears to be correctly moderating the node-age estimate based on the limited morphological divergence. Topologies are generally similar across analyses, but BEAST trees for crocodyliforms differ when clades are deeply nested but contain very old taxa. It appears that the constant-rate sampling assumption of the BDSS tree prior influences topology inference by disfavoring long, unsampled branches.
Data from: Empirical demonstration of hybrid chromosomal races in house mice
Western house mice (Mus musculus domesticus) and common shrews (Sorex araneus) are important models for study of chromosomal speciation. Both had ancestral karyotypes consisting of telocentric chromosomes, and each is subdivided into numerous chromosomal races many of which have resulted from fixation of new mutations (Robertsonian fusions and whole-arm reciprocal translocations). However, some chromosomal races in both species may alternatively have originated through hybridization, with particular homozygous recombinant products reaching fixation. Here, we demonstrate the process of generation of hybrid chromosomal races for the first time in either species using molecular markers. Analysis of centromeric microsatellite markers show that the Mid Valtellina (IMVA) and Upper Valtellina (IUVA) chromosomal races of the house mouse are recombinant products of hybridization of the Lower Valtellina (ILVA) and Poschiavo (CHPO) chromosomal races, supporting earlier theoretical analysis. IMVA and IUVA occupy a small area of the Italian Alps where ILVA makes contact with CHPO. IUVA and CHPO have previously been shown to be reproductively isolated in one village, emphasizing that hybrid chromosomal races in small mammals, as in plants, have the potential to be part of the speciation process.
Data from: Combined effects of natural enemies and competition for resources on a forest defoliator: a theoretical and empirical analysis
Explanations for the dynamics of insect outbreaks often focus on natural enemies, on the grounds that parasitoid and pathogen attack rates are high during outbreaks. While natural enemy models can successfully reproduce outbreak cycles, experiments have repeatedly demonstrated the importance of resource quality and abundance. Experiments, however, are rarely invoked in modeling studies. Here we combine mechanistic models, observational data, and field experiments to quantify the roles of parasitoid attacks and resource competition on the jack pine budworm, Choristoneura pinus. By fitting models to a combination of observational and experimental data, we show that parasitoid attacks are the main source of larval budworm mortality at low and intermediate budworm densities, but that resource competition is the main source of mortality at high densities. Our results further show that the effects of resource competition become more severe with increasing host tree age, and that the effects of parasitoids are moderated by strong competition between parasitoids for hosts. Allowing for these effects in a model of insect outbreaks leads to realistic outbreak cycles, while a host-parasitoid model without resource competition produces an unrealistic stable equilibrium. The effects of resource competition are modulated by tree age, which in turn depends on fire regimes. Our model therefore suggests that increases in fire frequency due to climate change may interact in complex ways with budworm outbreaks. Our work shows that resource competition can be as important as natural enemies in modulating insect outbreaks, while demonstrating the usefulness of high-performance computing in experimental field ecology.
Data from: The demographic history of populations experiencing asymmetric gene flow: combining simulated and empirical data.
Population structure can significantly affect genetic-based demographic inferences, generating spurious bottleneck-like signals. Previous studies have typically assumed island or stepping-stone models, which are characterized by symmetric gene flow. However, many organisms are characterized by asymmetric gene flow. Here, we combined simulated and empirical data to test whether asymmetric gene flow affects the inference of past demographic changes. Through the analysis of simulated genetic data with three methods (i.e. bottleneck, M-ratio and msvar), we demonstrated that asymmetric gene flow biases past demographic changes. Most biases were towards spurious signals of expansion, albeit their strength depended on values of effective population size and migration rate. It is noteworthy that the spurious signals of demographic changes also depended on the statistical approach underlying each of the three methods. For one of the three methods, biases induced by asymmetric gene flow were confirmed in an empirical multispecific data set involving four freshwater fish species (Squalius cephalus, Leuciscus burdigalensis, Gobio gobio and Phoxinus phoxinus). However, for the two other methods, strong signals of bottlenecks were detected for all species and across two rivers. This suggests that, although potentially biased by asymmetric gene flow, some of these methods were able to bypass this bias when a bottleneck actually occurred. Our results show that population structure and dispersal patterns have to be considered for proper inference of demographic changes from genetic data.
Data from: Concatenation and concordance in the reconstruction of mouse lemur phylogeny: an empirical demonstration of the effect of allele sampling in phylogenetics.
The systematics and speciation literature is rich with discussion relating to the potential for gene tree/species tree discordance. Numerous mechanisms have been proposed to generate discordance, including differential selection, long-branch attraction, gene duplication, genetic introgression, and/or incomplete lineage sorting. For speciose clades in which divergence has occurred recently and rapidly, recovering the true species tree can be particularly problematic due to incomplete lineage sorting. Unfortunately, the availability of multi-locus or "phylogenomic" data sets does not simply solve the problem, particularly when the data are analyzed with standard concatenation techniques. In our study, we conduct a phylogenetic study for a nearly complete species sample of the dwarf and mouse lemur clade, Cheirogaleidae. Mouse lemurs (genus, Microcebus) have been intensively studied over the past decade for reasons relating to their high level of cryptic species diversity, and although there has been emerging consensus regarding the evolutionary diversity contained within the genus, there is no agreement as to the inter-specific relationships within the group. We attempt to resolve cheirogaleid phylogeny, focusing especially on the mouse lemurs, by employing a large multi-locus data set. We compare the results of Bayesian concordance methods with those of standard gene concatenation, finding that though concatenation yields the strongest results as measured by statistical support, these results are found to be highly misleading. By employing an approach where individual alleles are treated as OTUs, we show that phylogenetic results are substantially influenced by the selection of alleles in the concatenation process.
Data from: Connectivity in grey reef sharks (Carcharhinus amblyrhynchos) determined using empirical and simulated genetic data
Grey reef sharks (Carcharhinus amblyrhynchos) can be one of the numerically dominant high order predators on pristine coral reefs, yet their numbers have declined even in the highly regulated Australian Great Barrier Reef (GBR) Marine Park. Knowledge of both large scale and fine scale genetic connectivity of grey reef sharks is essential for their effective management, but no genetic data are yet available. We investigated grey reef shark genetic structure in the GBR across a 1200 km latitudinal gradient, comparing empirical data with models simulating different levels of migration. The empirical data did not reveal any genetic structuring along the entire latitudinal gradient sampled, suggesting regular widespread dispersal and gene flow of the species throughout most of the GBR. Our simulated datasets indicate that even with substantial migrations (up to 25% of individuals migrating between neighboring reefs) both large scale genetic structure and genotypic spatial autocorrelation at the reef scale were maintained. We suggest that present migration rates therefore exceed this level. These findings have important implications regarding the effectiveness of networks of spatially discontinuous Marine Protected Areas to protect reef sharks.
Data from: Applicability of RAD-tag genotyping for inter-familial comparisons: empirical data from two cetaceans
Restriction site-Associated DNA tag (RAD-tag) sequencing has become a popular approach to generate thousands of SNPs used to address diverse questions in population genomics. Comparatively, the suitability of RAD-tag genotyping to address evolutionary questions across divergent species has been the subject of only a few recent studies. Here, we evaluate the applicability of this approach to conduct genome-wide scans for polymorphisms across two cetacean species belonging to distinct families: the short-beaked common dolphin (Delphinus delphis; n = 5 individuals) and the harbor porpoise (Phocoena phocoena; n = 1 individual). Additionally, we explore the effects of varying two parameters in the Stacks analysis pipeline on the number of loci and level of divergence obtained. We observed a 34% drop in the total number of loci that were present in all individuals when analyzing individuals from the distinct families compared to analyses restricted to intra-specific comparisons (i.e., within D. delphis). Despite relatively stringent quality filters, 3,595 polymorphic loci were retrieved from our inter-familial comparison. Cetaceans have undergone rapid diversification and the estimated divergence time between the two families is relatively recent (14 to 19 My). Thus, our results showed that, for this level of divergence, a large number of orthologous loci can still be genotyped using this approach, which is on par with two recent in silico studies. Our findings constitute one of the first empirical investigations using RAD-tag sequencing at this level of divergence and highlights the great potential of this approach in comparative studies and to address evolutionary questions.
Data from: Energy benefits and emergent space use patterns of an empirically parameterized model of memory-based patch selection
Many species frequently return to previously visited foraging sites. This bias towards familiar areas suggests that remembering information from past experience is beneficial. Such a memory-based foraging strategy has also been hypothesized to give rise to restricted space use (i.e. a home range). Nonetheless, the benefits of empirically derived memory-based foraging tactics and the extent to which they give rise to restricted space use patterns are still relatively unknown. Using a combination of stochastic agent-based simulations and deterministic integro-difference equations, we developed an adaptive link (based on energy gains as a foraging currency) between memory-based patch selection and its resulting spatial distribution. We used a memory-based foraging model developed and parameterized with patch selection data of free-ranging bison Bison bison in Prince Albert National Park, Canada. Relative to random use of food patches, simulated foragers using both spatial and attribute memory are more efficient, particularly in landscapes with clumped resources. However, a certain amount of random patch use is necessary to avoid frequent returns to relatively poor-quality patches, or avoid being caught in a relatively poor quality area of the landscape. Notably, in landscapes with clumped resources, simulated foragers that kept a reference point of the quality of recently visited patches, and returned to previously visited patches when local patch quality was poorer than the reference point, experienced higher energy gains compared to random patch use. Furthermore, the model of memory-based foraging resulted in restricted space use in simulated landscapes and replicated the restricted space use observed in free-ranging bison reasonably well. Our work demonstrates the adaptive value of spatial and attribute memory in heterogeneous landscapes, and how home ranges can be a byproduct of non-omniscient foragers using past experience to minimize temporal variation in energy gains.
Data from: Empirical targets for acute hemodynamic management of individuals with spinal cord injury
Objective: To determine the hemodynamic conditions associated with optimal neurological improvement in acute traumatic spinal cord injury (SCI) individuals who had lumbar intrathecal catheters placed to measure cerebrospinal fluid pressure (CSFP). Methods: Ninety-two acute SCI individuals were enrolled in this multi-center prospective observational clinical trial. We monitored mean arterial pressure (MAP) and CSFP during the first week post-injury, and assessed neurologic function at baseline and six-months post-injury. We used relative risk iterations to determine transition points at which the likelihood of either improving neurologically or remaining unchanged neurologically was equivalent. These transition points guided our analyses where we examined the linear relationships between time spent within target hemodynamic ranges (i.e., clinical adherence) and neurological recovery. Results: Relative risk transition points for CSFP, MAP, and spinal cord perfusion pressure (SCPP) were linearly associated with neurological improvement and directed the identification of key hemodynamic target ranges. Clinical adherence to the target ranges was positively and linearly related to improved neurological outcomes. Adherence to SCPP targets, not MAP targets, was the best indicator of improved neurological recovery, which occurred with SCPP targets of 60-65 mmHg. Failing to maintain the SCPP within the target ranges was an important detrimental factor in neurologic recovery, particularly if the target range is set lower. Conclusion: We provide an empirical, data-driven approach to aid institutions in setting hemodynamic management targets that accept the real-life challenges of adherence to specific targets. Our results provide a framework to guide the development of widespread institutional management guidelines for acute traumatic SCI.
Data from: The effects of inference method, population sampling and gene sampling on species tree inferences: an empirical study in slender salamanders (Plethodontidae: Batrachoseps)
Species tree methods are now widely used to infer the relationships among species from multi-locus datasets. Many methods have been developed, which differ in whether gene and species trees are estimated simultaneously or sequentially, and in how gene trees are used to infer the species tree. While these methods perform well on simulated data, less is known about what impacts their performance on empirical data. We used a dataset including five nuclear genes and one mitochondrial gene for 22 species of Batrachoseps to compare the effects of method of analysis, within-species sampling and gene sampling on species tree inferences. For this dataset, the choice of inference method had the largest effect on the species tree topology. Exclusion of individual loci had large effects in *BEAST and STEM, but not in MP-EST. Different loci carried the greatest leverage in these different methods, showing that the causes of their disproportionate effects differ. Even though substantial information was present in the nuclear loci, the mitochondrial gene dominated the *BEAST species tree. This leverage is inherent to the mtDNA locus and results from its high variation and lower assumed ploidy. This mtDNA leverage may be problematic when mtDNA has undergone introgression, as is likely in this dataset. By contrast, the leverage of RAG1 in STEM analyses does not reflect properties inherent to the locus, but rather results from a gene tree that is strongly discordant with all others, and is best explained by introgression between distantly related species. Within-species sampling was also important, especially in *BEAST analyses, as shown by differences in tree topology across 100 subsampled datasets. Despite the sensitivity of the species tree methods to multiple factors, five species groups, the relationships among these, and some relationships within them, are generally consistently resolved for Batrachoseps.
The spatiotemporal evolution and influencing factors of hotel industry in the metropolitan area: an empirical study based on China
Through the online booking platform, 10,543 big data of spatial and temporal distribution of Beijing hotel industry has been obtained in this paper. Then, the methods of GIS and the geographical detector are used to study the spatiotemporal evolution process and the influencing factors of Beijing hotel industry during 2003-2018. The results are as follows: a. During the period of 2003-2018, the hotel industry in Beijing maintained a high growth rate and had three growth peaks in 2008, 2010 and 2014. Meanwhile, major historical events, such as the Olympic Games had a significant influence on the development of the hotel industry. b. Between 2003 and 2018, the hotel industry in Beijing gradually developed from the centripetal agglomeration to aggregation + diffusion, and also from the single center to the multi-center. Besides, various hotels presented two characteristics of city orientation and scenic orientation. c. The natural geographical environment had shaped the overall pattern and characteristics of the spatial distribution of the hotel industry in Beijing, and the socio-economic factors such as commercial activities, public facilities, tourism services and traffic conditions significantly influenced the location selection of the hotel industry. Therefore, the urban center is the ideal area for the spatial layout of the hotel industry. d. Geographical detector research showed that the factors, such as administrative organs, road network density, leisure and recreational facilities, and companies have strong explanatory power for hotel location selection, which is an important reference index for hotels to select the micro location. This paper is a beneficial supplement to the existing research and has certain guiding significance for the sustainable development of Beijing hotel industry.
Data from: Spatial heterogeneity in landscape structure influences dispersal and genetic structure: empirical evidence from a grasshopper in an agricultural landscape
Dispersal may be strongly influenced by landscape and habitat characteristics that could either enhance or restrict movements of organisms. Therefore, spatial heterogeneity in landscape structure could influence gene flow and the spatial structure of populations. In the past decades, agricultural intensification has led to the reduction in grassland surfaces, their fragmentation and intensification. As these changes are not homogeneously distributed in landscapes, they have resulted in spatial heterogeneity with generally less intensified hedged farmland areas remaining alongside streams and rivers. In this study, we assessed spatial pattern of abundance and population genetic structure of a flightless grasshopper species, Pezotettix giornae, based on the surveys of 363 grasslands in a 430-km² agricultural landscape of western France. Data were analysed using geostatistics and landscape genetics based on microsatellites markers and computer simulations. Results suggested that small-scale intense dispersal allows this species to survive in intensive agricultural landscapes. A complex spatial genetic structure related to landscape and habitat characteristics was also detected. Two P. giornae genetic clusters bisected by a linear hedged farmland were inferred from clustering analyses. This linear hedged farmland was characterized by high hedgerow and grassland density as well as higher grassland temporal stability that were suspected to slow down dispersal. Computer simulations demonstrated that a linear-shaped landscape feature limiting dispersal could be detected as a barrier to gene flow and generate the observed genetic pattern. This study illustrates the relevance of using computer simulations to test hypotheses in landscape genetics studies.
When do agents outperform centralized algorithms? - A systematic empirical evaluation in logistics - datasets and results
<p>This directory contains the data and results that were used and obtained during the realization of the following paper:</p> <blockquote> <p>When do agents outperform centralized algorithms? - A systematic empirical evaluation in logistics. Rinde R.S. van Lon and Tom Holvoet. Journal of Autonomous Agents and Multi-Agent Systems (2017).</p> </blockquote> <p>At the time of writing the paper is not yet accepted, some of the details (e.g. title, date of publication) are subject to change. The code that has been used can be found in this repository: https://github.com/rinde/vanLon17-JAAMAS-code</p> <p>Note that unpacked, all files are about 5 GB in total.</p> <p>This directory has the following structure:</p> <p>- makefile - script that can be used to run the analyses. The most important commands are:<br> - all - runs all analyses.<br> - paper-deps - runs only the analyses that were directly used in the paper.<br> - additional-analysis - runs several additional analyses.</p> <p>- readme.txt - this file.</p> <p>- results - contains all R-scripts used to analyse the data<br> - data/main - contains the results of the main result.<br> - data/mas-tuning - contains the results of the MAS tuning experiments.<br> - data/optaplanner-tuning-gendreau - contains the results of the OptaPlanner tuning experiments.<br> - data/sensitivity - contains the results of the simulator sensitivity experiments (using OptaPlanner algorithms).</p> <p>- scenarios<br> - gendreau2006 - contains the dataset from the Gendreau et al. [1] paper, used for the OptaPlanner tuning experiments.<br> - mas-tuning-dataset - contains the dataset that was used for tuning the MAS. This was generated using the code from https://github.com/rinde/vanLon17-JAAMAS-code<br> - vanLonHolvoet15-adapted-to-4-hours - contains the dataset that was used for the main experiment. This is an adapted version of the dataset from [2]. This version has a duration of 4 hours and requires a real-time simulator. It was generated using the code from https://github.com/rinde/vanLon17-JAAMAS-code </p> <ul> <li>[1] Michel Gendreau, Francois Guertin, Jean-Yves Potvin, and René Séguin. Neighborhood search heuristics for a dynamic vehicle dispatching problem with pick- ups and deliveries. Transportation Research Part C: Emerging Technologies, 14 (3):157–174, 2006. ISSN 0968090X. doi:10.1016/j.trc.2006.03.002.</li> <li>[2] Rinde R. S. van Lon and Tom Holvoet. Towards systematic evaluation of multi-agent systems in large scale and dynamic logistics. In Qingliang Chen, Paolo Torroni, Serena Villata, Jane Hsu, and Andrea Omicini, editors, PRIMA 2015: Principles and Practice of Multi-Agent Systems: 18th International Conference, Bertinoro, Italy, October 26-30, 2015, Proceedings, pages 248–264. Springer In- ternational Publishing, Cham, 2015. ISBN 978-3-319-25524-8. doi:10.1007/978- 3-319-25524-8 16.</li> </ul>
Empirical orthogonal functions of daily rainfall measurements from TRMM
<p>(see README.md)</p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.